Triple
T18192162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elaine Hansen Hatch |
E435562
|
entity |
| Predicate | spouseTermEndInSenate |
P70424
|
FINISHED |
| Object | 2019 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 2019 | Statement: [Elaine Hansen Hatch, spouseTermEndInSenate, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseTermEndInSenate Context triple: [Elaine Hansen Hatch, spouseTermEndInSenate, 2019]
-
A.
spouseNumberOfTermsInOffice
Indicates the number of distinct terms in office that the spouse of the referenced entity has served.
-
B.
spouseOfficeEndTime
chosen
Indicates the time at which a spouse’s term or tenure in a particular office or position ends.
-
C.
spouseEndTime
Indicates the time or date at which a spousal relationship between two entities ends.
-
D.
spousePositionHeldStartTime
Indicates the date and time when a spouse first began holding a particular position or office.
-
E.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d05974819094b4a50d081be881 |
completed | April 19, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.